David Venet
Impact in
- Cancer Research top 1%
- Breast Cancer Treatment Studies
- Cancer Genomics and Diagnostics
- Oncology top 5%
- HER2/EGFR in Cancer Research
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
-
- Breast Cancer Treatment Studies 8
- Cancer Genomics and Diagnostics 7
- Oncology 12
- HER2/EGFR in Cancer Research 8
- Cancer Immunotherapy and Biomarkers 3
- Co-authors
- Vincent Detours (6 shared papers)Jacques E. Dumont (3 shared papers)Christos P. Sotiriou (22 shared papers)Françoise Rothé (19 shared papers)Yacine Barèche (4 shared papers)Michail Ignatiadis (8 shared papers)Martine J Piccart (8 shared papers)Philippe Georges Aftimos (2 shared papers)
In The Last Decade
David Venet
54 papers receiving 2.6k citations
David Venet's Hit Papers
Peers
Comparison fields: 5 of 67
- Cancer Research 727
- Oncology 463
- Statistics and Probability 82
- Molecular Biology 361
- Endocrinology, Diabetes and Metabolism 82
Countries citing papers authored by David Venet
This map shows the geographic impact of David Venet's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Venet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Venet more than expected).
Fields of papers citing papers by David Venet
This network shows the impact of papers produced by David Venet. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Venet. The network helps show where David Venet may publish in the future.
Co-authors
The 25 scholars most cited alongside David Venet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome Hit paper breakdown → | 2011 | 475 |
| 2 | 2018 | 299 | |
| 3 | 2019 | 158 | |
| 4 | 2021 | 141 | |
| 5 | 2016 | 132 | |
| 6 | 2019 | 106 | |
| 7 | 2001 | 100 | |
| 8 | 2023 | 92 | |
| 9 | 2017 | 77 | |
| 10 | 2012 | 74 | |
| 11 | 2018 | 69 | |
| 12 | 2022 | 66 | |
| 13 | 2020 | 65 | |
| 14 | 2024 | 64 | |
| 15 | 2005 | 58 | |
| 16 | 2005 | 51 | |
| 17 | 2015 | 51 | |
| 18 | 2023 | 49 | |
| 19 | 2012 | 37 | |
| 20 | 2020 | 34 |
About David Venet
David Venet is a scholar working on Cancer Research, Oncology, Statistics and Probability, Molecular Biology and Endocrinology, Diabetes and Metabolism, having authored 56 papers that have together received 2.6k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (8 papers), HER2/EGFR in Cancer Research (8 papers), Cancer Genomics and Diagnostics (7 papers), Statistical Methods in Clinical Trials (5 papers), Gene expression and cancer classification (4 papers), Cancer Immunotherapy and Biomarkers (3 papers), Thyroid Cancer Diagnosis and Treatment (3 papers) and PI3K/AKT/mTOR signaling in cancer (2 papers). The work is most often cited by research in Cancer Research (727 citations), Oncology (463 citations), Statistics and Probability (82 citations), Molecular Biology (361 citations) and Endocrinology, Diabetes and Metabolism (82 citations). David Venet has collaborated with scholars based in Belgium, Italy and France. Frequent co-authors include Vincent Detours, Jacques E. Dumont, Christos P. Sotiriou, Françoise Rothé, Yacine Barèche, Michail Ignatiadis, Martine J Piccart, Philippe Georges Aftimos, Carine Maenhaut and Hugues Bersini. Their work appears in journals such as Clinical Cancer Research, Nature Communications, Annals of Oncology, npj Breast Cancer and Bioinformatics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.